APPLICATION OF GIS IN MODELLING REAL TIME POPULATION EXPOSURE TO PM2.5

ZUBAIRU MOHAMMAD, JABIR ABUBAKAR

Abstract


Air pollution has caused many deaths globally across all age groups with most of the deaths attributed to PM2.5 which
is an extremely small sized particulate matter that can travels deep in to the lungs, hit the blood stream and affect the
respiratory track. This study has estimated Southampton spatiotemporal population exposure to air pollution using the
Surface builder (SB) 24/7 model and a modelled air pollution data from DEFRA with a specific focus on the variation in
the level of exposure to PM 2.5 by different population age groups, using GIS. After modeling the population exposure
the resulted map was resampled to 200m by 200m to match the spatial resolution of the output population distribution
model. The result shows that only few areas around the southern parts of the study areas (mostly residential areas
with low commercial activities) have low concentration of PM2.5 pollutant. The results further identified a significant
variation in the level of exposure by different population age groups with the population age group between the age of
18 to 64 (non-students) having the highest level of exposure at both 2am (55% of the exposed population) and 2pm
(52%). On the other hand, the age group with the lowest level of exposure (2%), at both times of the day, is 16 to 17
years of age. 18 to 64 years old students in higher education (HE) and people of over 65 years of age are second
subgroups highly exposed while the remaining age groups (0 to 4, 5 to 9, 10 to 15) show almost similar exposure (5 to
6%) in both times of the day. Overall, there is an incredible difference in exposure to PM2.5 by different age groups
which reflects the level of spatial interaction by each age group.


Keywords


Air pollution, population distribution model, surface builder 247, population age groups, PM2.5, spatiotemporal estimates

Full Text:

PDF

Refbacks

  • There are currently no refbacks.